Type I and II errors (1 of 2)

There
are two kinds of errors that can be made in
significance testing: (1) a true null
hypothesis can be incorrectly rejected and (2) a false null
hypothesis can fail to be rejected. The former error is called a Type
I error and the latter error is called a Type II error. These two
types of errors are defined in the table.

Statistical Decision

True State of the Null Hypothesis

H0 True

H0 False

Reject H0

Type I error

Correct

Do not Reject H0

Correct

Type II error

The probability of a Type I
error is designated by the Greek letter alpha (a) and is
called the Type I error rate; the probability of a Type II error (the
Type II error rate) is designated by the Greek letter beta (ß)
. A Type II error is only an error in the sense that an opportunity
to reject the null hypothesis correctly was lost. It is not an error
in the sense that an incorrect conclusion was drawn since no
conclusion is drawn when the null hypothesis is
not rejected.